quickstart

The sentences to fill `[MASK]` tokens in.

input

The maximum number of tokens to predict for each mask. Optional, defaults to 1.

max_tokens

This model can predict masked tokens in a sentence. For example, it might predict `capital` given `Paris is the [MASK] of France.`.

See [here](https://huggingface.co/bert-base-uncased) for more details.

The predicted tokens for each input sentence. This will have shape `[N, max_tokens]`, but some cells may be empty.

tokens

The scores for each predicted token. This will have shape `[N, max_tokens]`, but some cells may have a score of zero.

scores

A language model that can fill masked tokens in sentences

Carton

google-research / bert-base-uncased

Examples

quickstart

Inputs

Name: input

Outputs

Name: scores

Name: tokens

Usage

Inputs

Name: input

Description: The sentences to fill `[MASK]` tokens in.

Type: string

Shape: [N]

Name: max_tokens

Description: The maximum number of tokens to predict for each mask. Optional, defaults to 1.

Type: uint32

Shape: Scalar

Outputs

Name: tokens

Description: The predicted tokens for each input sentence. This will have shape `[N, max_tokens]`, but some cells may be empty.

Type: string

Shape: [N, *]

Name: scores

Description: The scores for each predicted token. This will have shape `[N, max_tokens]`, but some cells may have a score of zero.

Type: float32

Shape: [N, *]

Readme

Get it

Homepage

License

Tasks